Cell-cell Communication Networks Research Articles

S246: A HUMAN BONE MARROW ORGANOID FOR DISEASE MODELLING AND DRUG SCREENING IN BLOOD CANCERS

Background: Blood cancers are the most common cancer affecting children, and among the top 10 most common cancers in adults, in whom they remain largely incurable. In the era of advanced “omics”, a major bottleneck to the development of novel therapies is target prioritization and validation. There is a pressing need for experimental platforms that model the cellular and molecular complexity of the bone marrow niche, to enable mechanistic studies into the role of the bone marrow microenvironment in the initiation and propagation of blood cancers. Aims: Organoid technologies have been transformative in other settings, but an organoid with adequate homology to native haematopoietic tissues has not yet been reported. We therefore sought to develop organoids that emulate the cellular, molecular and spatial architecture of human bone marrow. Methods: A directed-differentiation protocol was devised in which human iPSCs formed mesodermal aggregates before hydrogel embedding and commitment to vascular and hematopoietic lineages. Multi-modal imaging and single cell RNA-sequencing were used to confirm cellular, molecular and architectural homology to native human hematopoietic tissues. Results: We optimized hydrogel compositions and cytokine cocktails to support the differentiation of a 3D bone marrow perivascular niche. The resulting organoids contained distinct haematopoietic stem/progenitor cells (HSPCs), stromal and myeloid cellular subtypes including pro-platelet forming megakaryocytes and lumen-forming vasculature. 3D whole-organoid imaging revealed a vascular network with sinusoid-like vessels invested with MSCs/fibroblasts (Fig1A), and the extravasation of haematopoietic cells into vessel lumens. Megakaryocytes closely associated with vessels, and extended pro-platelet protrusions into the vasculature with remarkable similarity to native bone marrow. scRNAseq analysis confirmed transcriptional homology to human bone marrow cellular subtypes, and highlighted strong cell-cell communication networks and haematopoietic support from organoid stroma. We first explored the utility of the organoids to model myelofibrosis, an exemplar malignancy that involves cancer-induced bone marrow remodelling and where there is a need for improved models for target prioritization and novel therapies. Treatment of organoids with TGFβ resulted in a dose-dependent increase in hallmarks of fibrosis (Fig 1B), which was effectively reversed using pharmacological agents, enabling drug screening. Given their homology to native bone marrow, we hypothesized that the organoids may support engraftment of primary human cells. Indeed, cells from healthy donors and patients with blood cancers efficiently engrafted throughout the organoids. After 14 days, organoids engrafted with myelofibrosis but not healthy cells showed dramatic fibrotic remodelling (Fig 1C). The organoids also supported primary cells from other myeloid and lymphoid blood cancers, including those notoriously difficult to maintain in vitro – e.g. myeloma cells engrafted into organoids were >90% viable at 10 days following seeding, while rapidly dying within 48 hrs without organoid support. The ability to study primary cells ex vivo overcomes a huge hurdle to translational research in the myeloma field. Image:Summary/Conclusion: This platform is an enabling technology for the interrogation of disease mechanisms in haematological disorders. Target identification and screening using a species-specific, 3D model that can incorporate primary patient cells will reduce dependence on animal models and may accelerate translational research.

Manual acupuncture at ST36 attenuates rheumatoid arthritis by inhibiting M1 macrophage polarization and enhancing Treg cell populations in adjuvant-induced arthritic rats.

Acupuncture has been found to be effective at relieving many inflammatory pain conditions, including rheumatoid arthritis (RA). We aimed to assess the anti-inflammatory potential of manual acupuncture (MA) treatment of RA using adjuvant-induced arthritic (AIA) rats and to explore the underlying mechanisms. The anti-inflammatory and analgesic actions of MA at ST36 (Zusanli) in AIA rats were assessed using paw withdrawal latency and swelling, histological examination and cytokine detection by enzyme-linked immunoassay (ELISA). The cell-cell communication (CCC) network was analyzed with a multiplex immunoassay of 24 immune factors expressed in the inflamed joints, and the macrophage and Treg populations and associated cytokines regulated by MA were investigated using reverse-transcription quantitative polymerase chain reaction (RT-qPCR), ELISA and flow cytometry. MA markedly decreased heat hyperalgesia and paw swelling in AIA rats. MA-treated rats also exhibited decreased levels of pro-inflammatory cytokines (tumor necrosis factor (TNF)-α, interleukin (IL)-1β) coupled with increased anti-inflammatory cytokines (IL-10, transforming growth factor (TGF)-β1) in the ankle joints at protein and mRNA levels. CCC network analysis confirmed that macrophages are of critical importance and are potential therapeutic targets in RA. Repeated treatment with MA triggered a macrophage phenotypic switch in the paws, with fewer M1 macrophages. Prominent increases in the Treg cell population and TGF-β1 in the popliteal lymph nodes demonstrated the immunomodulatory effects of MA. Furthermore, a selective TGF-β1-receptor inhibitor, SB431542, attenuated the anti-inflammatory effects of MA and MA-induced suppression of the levels of M1-released cytokines. These findings provide novel evidence that the anti-inflammatory and analgesic effects of MA on RA act through phenotypic modulation involving the inhibition of M1 macrophage polarization and an increase in the Treg cell population, highlighting the potential therapeutic advantages of acupuncture in controlling pain and ameliorating inflammatory conditions.

Mapping and Validation of scRNA-Seq-Derived Cell-Cell Communication Networks in the Tumor Microenvironment.

Recent advances in single-cell technologies, particularly single-cell RNA-sequencing (scRNA-seq), have permitted high throughput transcriptional profiling of a wide variety of biological systems. As scRNA-seq supports inference of cell-cell communication, this technology has and continues to anchor groundbreaking studies into the efficacy and mechanism of novel immunotherapies for cancer treatment. In this review, we will highlight methods developed to infer inter- and intracellular signaling from scRNA-seq and discuss how they have contributed to studies of immunotherapeutic intervention in the tumor microenvironment (TME). However, a central challenge remains in validating the hypothesized cell-cell interactions. Therefore, this review will also cover strategies for integration of these scRNA-seq-derived interaction networks with existing experimental and computational approaches. Integration of these networks with imaging, protein secretion measurements, and network analysis and mathematical modeling tools addresses challenges that remain with scRNA-seq to enhance studies of immunosuppressive and immunotherapy-altered signaling in the TME.

Nonlesional lupus skin contributes to inflammatory education of myeloid cells and primes for cutaneous inflammation.

Cutaneous lupus erythematosus (CLE) is a disfiguring and poorly understood condition frequently associated with systemic lupus. Previous studies suggest that nonlesional keratinocytes play a role in disease predisposition, but this has not been investigated in a comprehensive manner or in the context of other cell populations. To investigate CLE immunopathogenesis, normal-appearing skin, lesional skin, and circulating immune cells from lupus patients were analyzed via integrated single-cell RNA sequencing and spatial RNA sequencing. We demonstrate that normal-appearing skin of patients with lupus represents a type I interferon-rich, prelesional environment that skews gene transcription in all major skin cell types and markedly distorts predicted cell-cell communication networks. We also show that lupus-enriched CD16+ dendritic cells undergo robust interferon education in the skin, thereby gaining proinflammatory phenotypes. Together, our data provide a comprehensive characterization of lesional and nonlesional skin in lupus and suggest a role for skin education of CD16+ dendritic cells in CLE pathogenesis.

Parameterized Computational Framework for the Description and Design of Genetic Circuits of Morphogenesis Based on Contact-Dependent Signaling and Changes in Cell-Cell Adhesion.

Synthetic development is a nascent field of research that uses the tools of synthetic biology to design genetic programs directing cellular patterning and morphogenesis in higher eukaryotic cells, such as mammalian cells. One specific example of such synthetic genetic programs was based on cell-cell contact-dependent signaling using synthetic Notch pathways and was shown to drive the formation of multilayered spheroids by modulating cell-cell adhesion via differential expression of cadherin family proteins in a mouse fibroblast cell line (L929). The design method for these genetic programs relied on trial and error, which limited the number of possible circuits and parameter ranges that could be explored. Here, we build a parameterized computational framework that, given a cell-cell communication network driving changes in cell adhesion and initial conditions as inputs, predicts developmental trajectories. We first built a general computational framework where contact-dependent cell-cell signaling networks and changes in cell-cell adhesion could be designed in a modular fashion. We then used a set of available in vitro results (that we call the "training set" in analogy to similar pipelines in the machine learning field) to parameterize the computational model with values for adhesion and signaling. We then show that this parameterized model can qualitatively predict experimental results from a "testing set" of available in vitro data that varied the genetic network in terms of adhesion combinations, initial number of cells, and even changes to the network architecture. Finally, this parameterized model is used to recommend novel network implementation for the formation of a four-layered structure that has not been reported previously. The framework that we develop here could function as a testing ground to identify the reachable space of morphologies that can be obtained by controlling contact-dependent cell-cell communications and adhesion with these molecular tools and in this cellular system. Additionally, we discuss how the model could be expanded to include other forms of communication or effectors for the computational design of the next generation of synthetic developmental trajectories.

Spatially Annotated Single Cell Sequencing for Unraveling Intratumor Heterogeneity.

Intratumor heterogeneity is a major obstacle to effective cancer treatment. Current methods to study intratumor heterogeneity using single-cell RNA sequencing (scRNA-seq) lack information on the spatial organization of cells. While state-of-the art spatial transcriptomics methods capture the spatial distribution, they either lack single cell resolution or have relatively low transcript counts. Here, we introduce spatially annotated single cell sequencing, based on the previously developed functional single cell sequencing (FUNseq) technique, to spatially profile tumor cells with deep scRNA-seq and single cell resolution. Using our approach, we profiled cells located at different distances from the center of a 2D epithelial cell mass. By profiling the cell patch in concentric bands of varying width, we showed that cells at the outermost edge of the patch responded strongest to their local microenvironment, behaved most invasively, and activated the process of epithelial-to-mesenchymal transition (EMT) to migrate to low-confluence areas. We inferred cell-cell communication networks and demonstrated that cells in the outermost ∼10 cell wide band, which we termed the invasive edge, induced similar phenotypic plasticity in neighboring regions. Applying FUNseq to spatially annotate and profile tumor cells enables deep characterization of tumor subpopulations, thereby unraveling the mechanistic basis for intratumor heterogeneity.

Single-cell transcriptome analysis of Bisphenol A exposure reveals the key roles of the testicular microenvironment in male reproduction.

Testicular development during juvenile is crucial for subsequent male reproductive function. However, it remains poorly understood about the contribution of the testis microenvironment to human germ cell maturation. Therefore, we systematically analyzed scRNA-seq transcriptome and found the dramatic changes in cell-type composition in human testis during puberty. Then we constructed cell-cell communication networks between germ cells and somatic cells in the juvenile testis, which may be achieved via immune-related pathways. Our results showed that maturation-promoting factors are the switches of the Sertoli cells that drive sperm maturation. Furthermore, we found that Bisphenol A(BPA) enhanced the maturation and growth of germ cells through the Sertoli cell's secretory protein. Finally, our results indicate Bisphenol A would lead to the dysregulation of secreted protein expression in Sertoli cells during spermatogenesis, which in turn has direct cytotoxicity to Sertoli cells. Bisphenol A is one of the underlying causes of non-obstructive azoospermia (NOA). In summary, our results reveal the reproductive toxicity and molecular mechanism of Bisphenol A in Sertoli cells and male reproduction. Provide a reference for the toxicity of Bisphenol A to human reproduction.

The people behind the papers – Megan Rommelfanger and Adam MacLean

Cell fate decisions are dependent on both internal and external factors, but mathematical models of this process have often neglected the external signals. A new paper in Development describes a multiscale model that integrates intracellular gene regulatory networks with a cell-cell communication network at single-cell resolution. We caught up with the authors, PhD student Megan Rommelfanger and Adam MacLean, Assistant Professor at the University of Southern California, to find out more about their research.

Deciphering the Intercellular Communication Network of Peripartum Decidua that Orchestrates Delivery.

Intercellular communication in the decidua plays important roles in relaying information between the maternal and fetal systems in the maintenance of pregnancy and the transition to labor. To date, several studies have explored cell-cell communications in the decidua during different periods of pregnancy, but studies systematically decoding the intercellular communication network, its internal cascades, and their involvement in labor are still lacking. In this study, we reconstructed a decidual cell-cell communication network based on scRNA-seq of peripartum decidua via the CellCall method. The results showed that endometrial cells (EECs) and extravillous trophoblasts relayed most of the common intercellular signals in the decidua both before delivery (DBD) and after delivery (DAD). Endothelial cells and EECs controlled many WNT-signaling-related intercellular communication factors that differed between DBD and DAD, some of which could be candidate biomarkers for the diagnosis of labor. Analysis of intercellular communications related to T cells identified abundant maternal-fetal immune-tolerance-related communication, such as TNFSF14-TNFRSF14/LTBR and FASLG-FAS signalings. We further explored the characteristics of the B cell receptor (BCR) and T cell receptor (TCR) repertoires by single-cell BCR/TCR sequencing. The results showed no significant differences in clonal expansion of B/T cells between DAD and DBD, indicating there was no significant change to adaptive immunity at the maternal-fetal interface during delivery. In summary, the findings provide a comprehensive view of the intercellular communication landscape in the peripartum decidua and identified some key intercellular communications involved in labor and maternal-fetal immune tolerance. We believe that our study provides valuable clues for understanding the mechanisms of pregnancy and provides possible diagnostic strategies for the onset of labor.

Dissecting the single-cell transcriptome network in patients with esophageal squamous cell carcinoma receiving operative paclitaxel plus platinum chemotherapy

Esophageal squamous cell carcinoma (ESCC) accounts for 90% of all cases of esophageal cancers worldwide. Although neoadjuvant chemotherapy (NACT-ESCC) improves the survival of ESCC patients, the five-year survival rate of these patients is dismal. The tumor microenvironment (TME) and tumor heterogeneity decrease the efficacy of ESCC therapy. In our study, 113,581 cells obtained from five ESCC patients who underwent surgery alone (SA-ESCC) and five patients who underwent preoperative paclitaxel plus platinum chemotherapy (NACT-ESCC), were used for scRNA-seq analysis to explore molecular and cellular reprogramming patterns. The results showed samples from NACT-ESCC patients exhibited the characteristics of malignant cells and TME unlike samples from SA-ESCC patients. Cancer cells from NACT-ESCC samples were mainly at the ‘intermediate transient stage’. Stromal cell dynamics showed molecular and functional shifts that formed the immune-activation microenvironment. APOE, APOC1, and SPP1 were highly expressed in tumor-associated macrophages resulting in anti-inflammatory macrophage phenotypes. Levels of CD8+ T cells between SA-ESCC and NACT-ESCC tissues were significantly different. Immune checkpoints analysis revealed that LAG3 is a potential immunotherapeutic target for both NACT-ESCC and SA-ESCC patients. Cell–cell interactions analysis showed the complex cell-cell communication networks in the TME. In summary, our findings elucidate on the molecular and cellular reprogramming of NACT-ESCC and ESCC patients. These findings provide information on the potential diagnostic and therapeutic targets for ESCC patients.

Signaling Peptides Regulating Abiotic Stress Responses in Plants.

As sessile organisms, plants are exposed to constantly changing environments that are often stressful for their growth and development. To cope with these stresses, plants have evolved complex and sophisticated stress-responsive signaling pathways regulating the expression of transcription factors and biosynthesis of osmolytes that confer tolerance to plants. Signaling peptides acting like phytohormones control various aspects of plant growth and development via cell-cell communication networks. These peptides are typically recognized by membrane-embedded receptor-like kinases, inducing activation of cellular signaling to control plant growth and development. Recent studies have revealed that several signaling peptides play important roles in plant responses to abiotic stress. In this mini review, we provide recent findings on the roles and signaling pathways of peptides that are involved in coordinating plant responses to abiotic stresses, such as dehydration, high salinity, reactive oxygen species, and heat. We also discuss recent developments in signaling peptides that play a role in plant adaptation responses to nutrient deficiency stress, focusing on nitrogen and phosphate deficiency responses.

Abstract 130: Resolving the spatial and cellular architecture of lung adenocarcinoma by multi-region single-cell sequencing

Abstract Lung adenocarcinoma (LUAD) is the most commonly diagnosed histological subtype of lung cancer. While earlier work has underscored genomic and immune alterations in LUAD, the roles of individual cell populations in early-stage human LUAD evolution in space remain unknown. Here, we provide a detailed cellular atlas of early-stage LUAD and its spatial ecosystem along the peripheral lung. We performed single-cell RNA sequencing of 186,916 cells including enriched epithelial fractions from five early-stage LUADs with fourteen multi-region normal lung tissues of defined spatial proximities from the primary LUADs. We show that major epithelial and immune cellular lineages, states, and transcriptomic features geospatially and progressively evolve across normal regions and with increasing LUAD proximity. Analysis of 70,030 lung epithelial cells unraveled diverse lineage trajectories, transcriptional lineage plasticity programs underlying KRAS-mutant cells, and intratumoral heterogeneity within single sites. T regulatory cell programs including multiple immune checkpoints increased in tissues with closer proximity to LUADs, in sharp contrast to signatures of CD8+ cytotoxic T cells, antigen presentation by macrophages, and inflammatory dendritic cells. We found that some spatial signatures (e.g. a B cell signature score) were increased along the pathologic spectrum of normal lung, preneoplastic lesions, and matched invasive LUADs. LUAD cell-cell communication networks were enriched with ligand-receptor interactions involving CD24, LGALS9 and TIM3 immune checkpoints, including crosstalk between CD24 antigen in LUAD epithelial cells and SIGLEC10 in myeloid subsets. CD24 was markedly increased in preneoplasias relative to normal lung and further in LUAD, and its expression was highly positively correlated with immunosuppressive phenotypes. These data provide an atlas of cellular states and phenotypes underlying early-stage LUAD evolution in space, and a scalable resource for identification of targets for early treatment. Citation Format: Ansam Sinjab, Guangchun Han, Warapen Treekitkarnmongkol, Kieko Hara, Patrick Brennan, Minghao Dang, Dapeng Hao, Ruiping Wang, Enyu Dai, Hitoshi Dejima, Jiexin Zhang, Elena Bogatenkova, Beatriz Sanchez-Espiridion, Kyle Chang, Danielle R. Little, Samer Bazzi, Linh Tran, Kostyantyn Krysan, Carmen Behrens, Dzifa Duose, Edwin R. Parra, Maria Gabriela Raso, Luisa M. Solis, Junya Fukuoka, Jianjun Zhang, Boris Sepesi, Tina Cascone, Lauren A. Byers, Don L. Gibbons, Jichao Chen, Seyed Javad Moghaddam, Edwin J. Ostrin, Daniel G. Rosen, John V. Heymach, Paul Scheet, Steven Dubinett, Ignacio I. Wistuba, Junya Fujimoto, Christopher S. Stevenson, Avrum E. Spira, Linghua Wang, Humam Kadara. Resolving the spatial and cellular architecture of lung adenocarcinoma by multi-region single-cell sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 130.

Maximally selective single-cell target for circuit control in epilepsy models

Neurological and psychiatric disorders are associated with pathological neural dynamics. The fundamental connectivity patterns of cell-cell communication networks that enable pathological dynamics to emerge remain unknown. Here, we studied epileptic circuits using a newly developed computational pipeline that leveraged single-cell calcium imaging of larval zebrafish and chronically epileptic mice, biologically constrained effective connectivity modeling, and higher-order motif-focused network analysis. We uncovered a novel functional cell type that preferentially emerged in the preseizure state, the superhub, that was unusually richly connected to the rest of the network through feedforward motifs, critically enhancing downstream excitation. Perturbation simulations indicated that disconnecting superhubs was significantly more effective in stabilizing epileptic circuits than disconnecting hub cells that were defined traditionally by connection count. In the dentate gyrus of chronically epileptic mice, superhubs were predominately modeled adult-born granule cells. Collectively, these results predict a new maximally selective and minimally invasive cellular target for seizure control.

Systematic dissection of cytokine responses in vivo at single-cell resolution

Abstract Cytokines mediate a highly complex intercellular signaling network in health and disease. While many individual cytokines have been studied in-depth, we do not have a systems-level view of cell-type-specific responses to each cytokine and do not yet understand how cytokines orchestrate cell-cell communication networks in a complex immune response. To address these two gaps in cytokine biology, we performed single-cell RNA sequencing to measure gene expression profiles of over 20 mouse lymph node cell populations in response to over 80 cytokines in vivo. We first investigated how distinct cell types respond to the same cytokine and found that while some pathways are activated across multiple cell types, many cytokines induced cell-type-specific gene expression signatures. Next, we compared responses across cytokines and found that cytokines induced both unique and shared biological processes. For example, in NK cells, we found that IL-2/7/12/15/27/33/36a, IFN-a1/b/g/e/k, LIF, CT-1, and NP each induced a cytolytic program, but also cytokine-specific gene expression programs involved in antigen presentation, NF-kB activation, and mRNA splicing. Finally, based on our compendium of cytokine signatures, we created an algorithm to assess the level of cytokine responses and reconstruct cell-cell communication networks, and used this approach to uncover cytokine mediators in checkpoint blockade cancer immunotherapy treatment. Our study provides a global view of cell-type specific cytokine responses in vivo. The framework can be readily applied to other transcriptomic datasets for assessing the roles of cytokines and cell-cell communication networks in any immune response.

ST36 Acupuncture Alleviates the Inflammation of Adjuvant-Induced Arthritic Rats by Targeting Monocyte/Macrophage Modulation.

Background Rheumatoid arthritis (RA) is a chronic systemic chronic autoimmune disease characterized by the aggregation of immune cells and secretion of cytokines in the joint synovium, causing hyperblastosis and even bone destruction. Acupuncture has been proven effective in RA treatment. This study aimed to investigate the anti-inflammatory action of acupuncture, specifically, in relation to immune cell interactions and key mediators. Methods Rats with adjuvant-induced arthritics (AIA) were treated with manual acupuncture (MA) at Zusanli (ST36). Joint edema and paw withdrawal latency were monitored to observe the effects on inflammation. The levels of 24 cytokines, chemokines, and growth factors in ankle joints during the treatment (on days 1, 7, 15, and 21) were detected by multiplex immunoassay. A bioinformatics analysis based on a directed weighted mathematical model was used to construct cell communication network diagrams and identify the key cells through calculation. The monocyte/macrophage polarization in inflamed joints was investigated by detecting M1- and M2-phenotypic populations and their related cytokines. Results ST36 MA alleviated paw edema and upregulated the nociceptive threshold of AIA rats. Several innate and adaptive immune cytokines were dynamically regulated by MA, and MA-treated rats showed a significant improvement in symptoms compared with AIA rats by day 21. The immune cell-cell communication networks were intensified with the development of RA but were significantly reduced after treatment with MA. MA was found to specifically regulate monocytes/macrophages in inflamed ankle joints ST36 MA also inhibited M1-phenotype macrophages accompanied by decreased levels of IL-1β. Conclusions ST36 MA showed anti-inflammatory and analgesic effects as well as inhibition of immune cell communication networks in inflamed joints of AIA rats. Inhibiting the polarization of macrophages to the M1-phenotype in inflamed joints may be one of the key mechanisms of MA anti-inflammatory action. This research highlighted a systematic research paradigm for investigating mechanisms of acupuncture action.

Leveraging systems biology for predicting modulators of inflammation in patients with COVID-19.

Dysregulations in the inflammatory response of the body to pathogens could progress toward a hyperinflammatory condition amplified by positive feedback loops and associated with increased severity and mortality. Hence, there is a need for identifying therapeutic targets to modulate this pathological immune response. Here, we propose a single cell-based computational methodology for predicting proteins to modulate the dysregulated inflammatory response based on the reconstruction and analysis of functional cell-cell communication networks of physiological and pathological conditions. We validated the proposed method in 12 human disease datasets and performed an in-depth study of patients with mild and severe symptomatology of the coronavirus disease 2019 for predicting novel therapeutic targets. As a result, we identified the extracellular matrix protein versican and Toll-like receptor 2 as potential targets for modulating the inflammatory response. In summary, the proposed method can be of great utility in systematically identifying therapeutic targets for modulating pathological immune responses.

Gene regulatory network analysis identifies key genes and regulatory mechanisms involved in acute myocardial infarction using bulk and single cell RNA-seq data.

Cardiovascular and cerebrovascular diseases are leading causes of death worldwide, accounting for more than 40% of all deaths in China. Acute myocardial infarction (AMI) is a common cardiovascular disease and traditionally divided into ST-segment (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI), which are known with different prognoses and treatment strategies. However, key regulatory genes and pathways involved in AMI that may be used as potential biomarker for prognosis are unknown. In this study, we employed both bulk and single-cell RNA-seq to construct gene regulatory networks and cell-cell communication networks. We first constructed weighted gene co-expression networks for differential expressed genes between STEMI and NSTEMI patients based on whole-blood RNA-seq transcriptomics. Network topological attributes (e.g., node degree, betweenness) were analyzed to identify key genes involved in different functional network modules. Furthermore, we used single-cell RNA-seq data to construct multilayer signaling network to infer regulatory mechanisms of the above key genes. PLAUR (receptor for urokinase plasminogen activator) was found to play a vital role in transducing inter-cellular signals from endothelial cells and fibroblast cells to intra-cellular pathways of myocardial cells, leading to gene expression involved in cellular response to hypoxia. Our study sheds lights on identifying molecular biomarkers for diagnosis and prognosis of AMI, and provides candidate key regulatory genes for further experimental validation.

Inference of Ligand-Receptor Pairs from Single-Cell Transcriptomics Data.

Cell-cell communication is crucial for development and tissue homeostasis in multicellular organisms. Single-cell transcriptomics has emerged as a revolutionary technique for dissecting cellular compositions and potential cell-cell communication events via ligand-receptor pairs. To provide a systematic characterization of intercellular communication, we developed a framework to map cell-cell communication events mediated by ligand-receptor interactions across different cell types using single-cell transcriptomics data. Our repository of ligands, receptors and their interactions is integrated with a computational approach to identify cell-type specific and biologically relevant interactions. Here, we summarize the structure and content of our repository and present a practical guide for inferring cell-cell communication networks from single-cell RNA sequencing data.

Single-cell transcriptomic profiling provides insights into the toxic effects of Zearalenone exposure on primordial follicle assembly.

Rationale: Zearalenone (ZEN), a pollutant in our daily diet, seriously threatens the reproductive health of humans and animals. The primordial follicle (PF) assembly in the mouse occurs during the perinatal period, which determines the whole ovarian reserve in reproductive lifespan. In the current investigation, we administered ZEN orally to perinatal mice from 16.5 days post coitum (dpc) to postnatal day 3 (PD3), and single-cell RNA sequencing (scRNA-seq) was performed on PD0 and PD3 ovarian tissues in the offspring to check ZEN toxic to primordial follicle formation at the single cell level.Methods: Ovarian tissues (in vivo) were examined by single cell RNA sequencing analysis, Immunostaining, and Western blotting. Ovarian tissues (in vitro) were examined by qRT-PCR, Immunostaining, and Western blotting.Results: We found that ZEN exposure altered the developmental trajectory of both germ cells and granulosa cells. Furthermore, after establishing the cell-cell communication network between germ cells and granulosa cells, we found that this was perturbed by ZEN exposure, especially during the Hippo signaling pathway.Conclusions: This study showed that ZEN affected the status of germ cells and granulosa cells through the Hippo signaling pathway and blocked the assembly of PFs. This research contributes to our deeper understanding of the mechanisms of toxicity in different cell types and the disruption of normal intercellular signaling by ZEN exposure.

Abstract PO-043: Plexiform neurofibroma microenvironment at single-cell resolution

Abstract Plexiform neurofibromas (PN) are benign nerve sheath Schwann cell tumors, which occur in at least 50% of individuals with loss of function mutations in the NF1 tumor suppressor gene, an off signal for RAS-GTPases. Tumors form, at least in part, through activation of the RAS-MAPK pathway in Schwann cells. Though benign, PN can cause significant morbidity and are often inoperable due to integration with vital peripheral nerves. Recent clinical trials have shown that MEK inhibition can shrink most PN, but continued MEK inhibition is required for sustained response. It is recognized that PN contain many cell types in addition to Schwann cells, and that Schwann cells are present in varying proportions. However, biomarkers for many cell types have not yet been identified, and it is not known whether subpopulations of certain cell types exist within neurofibromas. To address these issues, we performed single cell RNA sequencing on PN using a genetically engineered mouse model which closely recapitulates human PN. We have characterized tumor composition, and identified PN Schwann cells, satellite glial cells, endothelial cells, fibroblasts, macrophages, T cells, dendritic cells, and other previously unreported cell types. We identified multiple subpopulations of Schwann cells, macrophages and fibroblasts within benign PN. Cluster by cluster comparison of PN to age-matched healthy nerve and to pretumor nerve tissue from the same mouse model revealed gene regulatory networks that are significantly altered in PN, after loss of NF1 function. Further, inference of cell-cell communication networks shows robust changes in PN that are absent before tumors form, and that are potentially targetable. Comparison to MEK inhibitor treated PN and to human PN sc-RNASeq is ongoing. Taken together, these approaches characterize PN, provide potential biomarkers for cell populations and identify targets for drug treatment. Supported by NIH (NINDS-28840) and the DOD Program on Neurofibromatosis. LK is supported by NIH Ruth L. Kirschstein T32. Citation Format: Leah J. Kershner, Jianqiang Wu, Nathan Salomonis, Nancy Ratner. Plexiform neurofibroma microenvironment at single-cell resolution [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-043.